SPE Distinguished Lecturer Program
The SPE Distinguished Lecturer Program is funded principallyThe SPE Distinguished Lecturer Program is funded principally through a grant from the SPE Foundation.
The society gratefully acknowledges the companies that supportThe society gratefully acknowledges the companies that support this program by allowing their professionals to participate as lecturers.
Special thanks to the American Institute of Mining, Metallurgical, and Petroleum Engineers (AIME) for its contribution to the program.p g
Society of Petroleum Engineers Distinguished Lecturer Programwww.spe.org/dl
Value of SeamlesslyValue of Seamlessly Collaborative Integrated Studies
Presented byYasin Senturk
Principal ProfessionalPetroleum Engineering and Development
Saudi Aramco Oil Company
Society of Petroleum Engineers
Saudi Aramco Oil CompanyDhahran, Saud Arabia
Society of Petroleum Engineers Distinguished Lecturer Programwww.spe.org/dl
OUTLINE
IntroductionObjectivePremise of Collaborative StudiesPremise of Collaborative Studies Critical Resources/Drivers
Q lifi d P f i l M (Mi d )Qualified Professional Manpower (Minds)Multidisciplinary “Know-How” (Expertise)I t t d D i i A l i (IDA) Th PIntegrated Decision Analysis (IDA) - The Process, Bases and Methodology
Conclusions : A Corporate Check List
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 33
Conclusions : A Corporate Check List
IntroductionSequential vs. Collaborative ProcessesSequential vs. Collaborative Processes
Sequential “Asset Team” Approach (Late 1980’s)
Exploration& Delineation
ReservesAssessment
ReservoirDevelopment &
Management
ProductionOperations
Processing & Sales
Sub-Optimal Solutions
Seamlessly “Collaborative Team” Approach (During 2000’s)
ProcessingProcessing& Sales
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 44
Parallel workflows & synergies captured: Optimal Solutions. l
ObjectiveCreate Value and Maximize Shareholders’ Wealthth h S i i i d t l d d t b
j
through Synergizing minds, tools and database.
HOW?Educate, Recruit, Develop and Retain Qualified Professional WorkforceIntegrate Multidisciplinary “Know- How”* to carry out appropriate studies to help make
ti l i t t d i irational investment decisions.
*
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 55
* Defined as Core Competencies/Expertise in Technical, Business and Leadership Skills l
Collaborative StudiesThe Premise
AB
The Premise
BCD
Decisions
AB
Focus only on what mattersXX
XX
XBCD
Work in parallel with faster tools
XX X
X
Work in parallel with faster toolsABC Improved Resources Utilization &
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 66
CD
p o ed esou ces Ut at o &Substantial Savings in Time l
Collaborative StudiesKey Attributes
Multi-disciplinary / Cross-Functional Teams
Key Attributes
Multi-disciplinary / Cross-Functional TeamsDedication & FocusParallel WorkflowsFull Spectrum of AlternativespB-i-C Integrated Decision Analysis (IDA)B tt & F t R lt d D i iBetter & Faster Results and DecisionsSynergy (Minds, Tools & Database) l
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 77
Collaborative StudiesSynergies Captured: Minds, Tools & DatabaseSynergies Captured: Minds, Tools & Database
l
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 88
Critical Resources / Drivers
Qualified Professionals: MindsKey Attributes Education Learning & Development (L&D)Key Attributes, Education, Learning & Development (L&D)
Multidisciplinary “Know-How” : Expertise
I t t d D i i A l i (IDA) P ttiIntegrated Decision Analysis (IDA): Putting it all together to capture synergies of Minds, T l d D t b
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 99
Tools and Database
Qualified ProfessionalsKey AttributesKey Attributes
Successful Professional Jasper King, The Way Ahead, SPE
AmbitiousR lt O i t d
p g yPublication (Vol.3, No.1, 2007)
Results-OrientedTechnically ProficientTeam PlayerEffective CommunicatorBusiness Savvy
Summary: Possess Technical Business & Leadership Skills
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 1010
Summary: Possess Technical, Business & Leadership Skills
Qualified Professionals…University Education: Rethink & Reengineer
Economic Evaluation of a Typical Oil Producing Property16 000 1 400
University Education: Rethink & Reengineer
12,000
14,000
16,000
1,000
1,200
1,400
MM
$)
Cum Costs
The Key Hypothesis*
8,000
10,000
ate
(ST
B/D
ay)
600
800
nd C
ash
Flow
s (MRate
Cum NCF @ 0%Cum NCF @ 10%
Q vs. t
l
2 000
4,000
6,000
Oil
Ra
0
200
400
Cum
Cos
ts a
n l
0
2,000
1 3 5 7 9 11 13 15 17 19 21 23 25
Years
-200
0
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 1111
* How learning the topic like porosity (e.g. reserves) is going to contribute to this bottom line must be emphasized.
Qualified Professionals…L&D – Competency Development Cycle
Create Personal Skill InventoryDefine
Set / Review
L&D Competency Development Cycle
E i t
Create Personal Skill Inventory(Discipline Specific)
Set / ReviewPersonal Goals &Business Needs
R i Assess
l
EnvironmentConducive for
Quality Learning &
ReviewAssess Effectiveness
& Create PersonalSkills Inventory
AssessIdentify Development Needs & Skills GAP
Development (L&D)Plan
Prepare/Modify
y
Execute Prepare/ModifyDevelopmentAction Plan
ImplementDevelopment
Actions
CoursesPlanned Work ExperiencesSpecial Job Assignments
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 1212
Adapted from “ Oxy’s input to PetroSkills (2004 Conclave, Houston, TX)”
Qualified Professionals…L&D - Career Progression & Value Added
Principal
L&D Career Progression & Value Added
Staff
Consultant
VALUE(Performance
Delivery)
Specialist
SeniorDelivery)
ResultsScope ,Impact
Discipline Junior
p , p& Influence
Measures Progress & Sets Expectations for Performance Delivery l
Core Competencies
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 1313
Adapted from “ Unocal’s input to PetroSkills (2004 Conclave, Houston, TX)”
Critical Resources / Drivers
Qualified Professionals - Minds
Multidisciplinary “Know-How” - ExpertiseTechnical, Business and Leadership Skills
Integrated Decision Analysis (IDA)
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 1414
Multi-Disciplinary “Know-How”
Three (3) Core Competencies / Expertise:
p y
Technical Specialties/SkillsEarth Sciences – Geology & GeophysicsEarth Sciences Geology & Geophysics
Petrophysics
Engineering - Drilling & Completion, Reservoir, Production & Facilitiesg g
Statistics & Decision Analysis
Maintenance & Operations, etc.
Business Skills - Economics & Finance
Leadership Skills K l d Sh i C i ti
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 1515
Leadership Skills – Knowledge Sharing, Communication, Impact & Influence, etc l
Critical Resources / Drivers
Qualified Professionals - Minds
Multidisciplinary “Know How” E tiMultidisciplinary “Know-How” - Expertise
Integrated Decision Analysis (IDA)S i t d th Mi d D t b & T lSynergies captured thru Minds, Database & Tools
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 1616
Integrated Decision Analysis (IDA) The Process – A Pictorial View
Geological Geological M d lM d l
Data AcquisitionData AcquisitionSimulation
The Process A Pictorial View
ModelModel
Database
Simulation Model
Database
Interpretation & ModelingInterpretation & Modeling
Technical Analysis D i i A l i
Interpretation & ModelingInterpretation & Modeling
Technical Analysis• Multiple Realizations• Reserves• Development Options
Decision Analysis Plans for Execution
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 1717
Development Options
Business Modell
Integrated Decision Analysis (IDA)The Process – A Conceptual PremiseThe Process A Conceptual Premise
Reservoir Characterization,Modeling & Simulation
(Multiple Realizations – Volumes & Profiles)
TECHNICAL ANALYSIS
Evaluation of Alternatives, including Risk Analysis
Data & Knowledge
M t
Evaluation of Alternatives, including Risk Analysisincluding Risk Analysis
(Reserves, Development Plans and Producing Strategies)
DECISION ANALYSIS
Management(Acquisition & Learning)
DATABASE
including Risk Analysis(Reserves, Development Plans
and Producing Strategies)
Planning and Field
Implementation
DECISION ANALYSISPlanning and Field
Implementation
DECISION ANALYSIS
l
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 1818
ACTION PLANACTION PLANl
Integrated Decision AnalysisTechnical Issues – Key Parameters
With Significant Impact on Results:
Technical Issues Key Parameters
Proper PhysicsDetails - Grid Size, Number of Layers eta s G d S e, u be o aye sPetrophysical-based Rock TypingINPUT DATA Quality Static and DynamicINPUT DATA Quality – Static and DynamicInitialization – How to propagate & distribute data?data?Simultaneous Nodal Analysis (Reservoir, Completion Wellbore & Surface) l
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 1919
Completion, Wellbore & Surface) l
Integrated Decision Analysis Technical - Location of Trapped Oil Example
Water Cut and Pressure Match
Sw Profile
Technical Location of Trapped Oil Example
lWater Cut and Pressure Match
Well Log
Simulator
l
New Well
Delta Sw in 30 Years(14 Layer Model; 53,000 cells)
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 2020
Delta Sw in 30 Years(128 Layer Model; 1.4 million cells)SPE 71628 Pavlas
Integrated Decision AnalysisTechnical - Quantifying UncertaintyTechnical Quantifying Uncertainty
100% 5%
80%
100%
4%
5%
bilit
y ≥ Mean=28
Average or Expected Value (EV)
40%
60%
2%
3%
babi
lity
ePr
obab
50% l
20% 1%
Prob
mul
ativ
e
SD-Variability/Risk0%
-40 -20 0 20 40 60 80 1000%
Reserves (MMSTB) / Value (MM$)
Cu 16 28
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 2121
Risk Profile & Expectation Curve
Integrated Decision AnalysisTechnical - Reserves Assessment (Static)
Volumetric Equation: EUR = [A x h x Ø x (1- Swi) / FVF] x RFModeMode Most likely (Mode)Most likely (Mode)
Technical Reserves Assessment (Static)
Random Variables(Probability Distributions) Pr
obab
ility
Swi
Log-Normal
Mode
Mean
Prob
abili
ty
Swi
Log-Normal
Mode
Mean
Prob
abili
ty
AhTriangular
Most likely (Mode)
Min Max
Prob
abili
ty
AhTriangular
Most likely (Mode)
Min Max
RFUniform
Prob
abili
ty Min Max
RFUniform
Prob
abili
ty Min Max
Prob
abili
ty
Mean & Mode
PorosityNormal
Prob
abili
ty
Mean & Mode
PorosityNormal
Fixed ParametersVolumetric Model
g Ng N TriangularTriangular
lity
Mode
Mean
lity
Mode
Mean
Expectation Curve1.00.9
babi
lity ≥
Prob
abil
Prob
abil
OOIP0.1
0.5
1P 2P3PC
um. P
rob
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 2222
ReservesReserves Reserves0
l
Integrated Decision AnalysisTechnical - Reserves Assessment (Dynamic)
Production Profile Relaizations
Technical Reserves Assessment (Dynamic)
12,000
13,500
15,000
60
75
TB
)
7 500
9,000
10,500
STB
/Day
)
45
uctio
n (M
MST
l
4,500
6,000
7,500
Oil
Rat
e (S
30
mul
ativ
e Pr
od
Exaggerated Scales
0
1,500
3,000
0
15 CumExaggerated Scales
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 2323
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65
Years
Integrated Decision AnalysisTechnical - Reserves Assessment (Dynamic)
100% Distribution fitSi l t d li ti
P90
Technical Reserves Assessment (Dynamic)ba
bilit
y Simulated realization
P50B t T h i l S i
ve P
rob
Mean
Best Technical Scenario
50% Production Profile Relaizations
12,000
13,500
15,000
60
75
B)
Production Profile Relaizations
12,000
13,500
15,000
60
75
B)
mul
ativ
P10Model Results
0
1,500
3,000
4,500
6,000
7,500
9,000
10,500
12,000
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65
Oil
Rat
e (S
TB
/Day
)
0
15
30
45
60
Cum
ulat
ive
Prod
uctio
n (M
MST
B
0
1,500
3,000
4,500
6,000
7,500
9,000
10,500
12,000
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65
Oil
Rat
e (S
TB
/Day
)
0
15
30
45
60
Cum
ulat
ive
Prod
uctio
n (M
MST
B
l
0%0 20 40 60 80 100 120 140 160
Cu YearsYears
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 2424
Oil Recovery (MMSTB)
Integrated Decision Analysis Business Issues - Sustainable Earnings Growth
Growth Objective
Business Issues Sustainable Earnings Growth
($)
Net Earnings
jfor
Corporate Earnings(with New Investments)
Ear
ning
s (
P j d E i
Net Earningsrequired to meet
Objectives in year Ti
Ann
ual E Projected Earnings
from Existing Projects(no further Investment)
Time (Years)
A
TiNow 20 40l
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 2525
Earnings Gap Analysis (Newendorp & Schuyler, 2000)
Integrated Decision Analysis Business - Corporate ObjectivesBusiness Corporate Objectives
Maximize shareholders’ value (SHV) whileminimizing exposure to loss; andensuring earnings growth at a stipulated rate
Preferable when the Corporationmakes Profit each year,makes Profit each year,
stabilizes Profit and sustainable Growth,
maintains Liquidity and Solvency andmaintains Liquidity and Solvency, and
is a good Corporate Citizen. l
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 2626
Integrated Decision Analysis Business - How to Maximize SHV?
Maximize Market Value Added (MVA)
Business How to Maximize SHV?
( )MVA = Market Value (MV) – Book Value (BV)
M i i (MV BV) R ti th ki ti dMaximize (MV:BV) Ratio thru making continuous and sound new investments
8
Balance Sheet explains 15%(1/6) of Value Added only.
4
6
8
V) R
atio
6 to 1
1 to 1
S&P 500
Remaining 85% (5/6) byTalent & Intelligent Assets l
0
2
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
(MV/
BV
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 2727
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
Years
Integrated Decision Analysis Business - Valuation/Appraisal Model
Has Appropriate Business Model
Business Valuation/Appraisal Model
Accounts for the Time Value of Money ConceptQuantifies Judgments about Uncertainty andQuantifies Judgments about Uncertainty andincorporates the Risks in project cash flows.Uses realistic Company Discount Rate (or MARR)Uses realistic Company Discount Rate (or MARR)Has a Figure of Value, the best value measure:
NPV @ MARR % (Deterministic Analysis)NPV @ MARR % (Deterministic Analysis)EMV @ MARR % (Probabilistic Analysis)
D i i R l A t if P j t NPV EMV≥ 0 l
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 2828
Decision Rule: Accept if Project NPV or EMV≥ 0 l
Integrated Decision Analysis Business - Cash Flow based Valuation Model
Net Cash Flow (NCF)
Business Cash Flow based Valuation Model
Income Taxes
Costs Revenue
OPEX CAPEX
• Drilling Platforms & Wells• Fixed Costs (Labor)
ProductionTaxes
• Drilling – Platforms & Wells• Well Flowlines• Production & Injection Facilities• Oil & Gas Pipelines l
• Fixed Costs (Labor)• Variable Costs
- Lifting Costs- Electricity
Etc
Royalty
Production
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 2929
- Etc.Profiles
Integrated Decision Analysis Business - Evaluation Methods (How?)
Deterministic Methods
Business Evaluation Methods (How?)
Deterministic MethodsDCF Analysis and NPV ProfilesSensitivity AnalysisSensitivity Analysis
Probabilistic MethodsDecision Tree AnalysisMonte Carlo Simulation
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 3030
Deterministic ApproachComparing Projects by NPV ProfilesComparing Projects by NPV Profiles
800Key Prof it abilit y Measures Sum m ary
600
700 Project A Increm ent alProject A Project B Project (A - B)
Investment Capital (MM$) 300 200 100NPV @ 10% (MM$) 416 205 211DCF - ROR (%) 46% 53% 39%
300
400
500C O (%)
l
100
200
300
RORB = 53%
RORA = 46%
ROR(A-B) = 39%Project B
MARR=10%
-100
0
100Incremental Project
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 3131
-1000 10 20 30 40 50 60
Nominal Discount Rate (%)
Integrated Decision Analysis Business - Evaluation Methods (How?)
Deterministic Methods
Business Evaluation Methods (How?)
Deterministic MethodsDCF Analysis and NPV ProfilesSensitivity AnalysisSensitivity Analysis
Probabilistic MethodsDecision Tree AnalysisMonte Carlo Simulation
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 3232
Deterministic ApproachSensitivity Analysis – “Project A” NPVy y j
Tornado Diagram for a Typical Oil & Gas Producing PropertyS i i i f P j NPV Ch i h
Oil Price
Sensitivity of Project NPV to Changes in the Key ParametersParameter
+30%-30%
Discount Rate
$28/bbl $52/bbl$40/bbl
13% 7%10%
-30%+30%
l
CAPEX +30% -30%
13% 7%10% l
OPEX +30% -30%416 MM $
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 3333
250 300 350 400 450 500 550 600Net Present Value, NPV (Million $)
Integrated Decision Analysis Business - Evaluation Methods (How?)
Deterministic Methods
Business Evaluation Methods (How?)
Deterministic MethodsDCF Analysis and NPV ProfilesSensitivity AnalysisSensitivity Analysis
Probabilistic MethodsDecision Tree AnalysisMonte Carlo Simulation
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 3434
Decision Tree Analysis“Project A” Expected Value EstimatesProject A Expected Value Estimates
NPV @ 10% EMV @ 10%Reserves Size
(MMSTB)
0.380
NPV @ 10% EMV @ 10%
$200 MM $60 MM
(MMSTB)
1200.6$370 MM $400 MM $240 MM
2000.1
$700 MM $70 MM
$370 MMEV of Reserves
EMV of the Project A
116 MMSTBEMV = $370 MM (probabilistic) versus
NPV = $416 MM (deterministic)
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 3535
NPV $416 MM (deterministic)
Decision Rule: Higher the EMV better the project profitability. l
Integrated Decision Analysis Business - Evaluation Methods (How?)
Deterministic Methods
( )
Deterministic MethodsDCF Analysis and NPV ProfilesSensitivity AnalysisSensitivity Analysis
Probabilistic MethodsDecision Tree AnalysisMonte Carlo Simulation
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 3636
Monte Carlo Simulation“Project A” NPV Risk Profile
y
Mean & Mode
y
Mean & ModeMode Mode
y
Most likely (Mode)
y
Most likely (Mode)
ty
Mean & Mode
ty
Mean & Mode
y
Mean & Mode
y
Mean & Mode
NCFt = Volumet x Pricet – Royaltyt – OPEXt – CAPEXt - Taxest
Project A NPV Risk ProfilePr
obab
ility
Volume
Prob
abili
ty
Volume
Prob
abili
ty
CAPEX
Mean
Prob
abili
ty
CAPEX
Mean
Prob
abili
ty
Prices
Min Max
Prob
abili
ty
Prices
Min Max
Prob
abili
t
OPEX
Prob
abili
t
OPEX
Prob
abili
ty
Taxes
Prob
abili
ty
Taxes
Cash Flow Model Fixed Parameters(Deterministic)
100% 50%Mean & SD≥
60%
80%
ve P
roba
bilit
y
30%
40%
babi
lity
Mean & SDEMVA = $385 MM
SDA = $200 MM
50%
≥
Profile with an EMV of $385 MM as compared to l
0%
20%
40%
Cum
ulat
iv
0%
10%
20%Pr
o
350
tnt
∑=
pSingle NPV Estimate of $416 MM
l
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 3737
%-200 0 200 400 600 800 1000
Net Present Value, NPV @ 10% (MM$)
% t
t
t MARRNCFNPV )1/(%10@
0
+=∑=
Probabilistic AnalysisComparing and Ranking Projects
50%
Comparing and Ranking Projects
40%
y
EMVB = $450
EMVA = $385
20%
30%
Prob
abili
ty
0%
10% SDA=$200 SDB=$100
0%-200 0 200 400 600 800 1000
Net Present Value, NPV @ 10% (MM$)
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 3838
Decision: Project B is clearly superior to Project A. l
Probabilistic AnalysisComparing and Ranking ProjectsComparing and Ranking Projects
50%
EMVA = $385 30%
40%
ty
EMVC = $190
20%
30%
Prob
abili
SDA=$200SDC=$80
0%
10%
0%-200 0 200 400 600 800 1000
Net Present Value, NPV @ 10% (MM$)
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 3939
2) For a risk-averse investor, it is not clear & further analysis required. lDecision: 1) For a risk-neutral investor, Project A is better than Project C.
Probabilistic AnalysisComparing Projects - Risk Neutral vs AverseComparing Projects Risk Neutral vs. AverseRisk Adjusted Value, RAV =EMV – σ2
NPV/(2B)50%
Project A40%
y
RAV = $330
EMV = $385
Project A
20%
30%
Prob
abili
ty
0%
10%SD=$200SD=$150
D i i R l F i B d t (B) th hi h th RAV b tt i
0%-200 0 200 400 600 800 1000
Net Present Value, NPV @ 10% (MM$)
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 4040
Decision Rule: For a given Budget (B), the higher the RAV, better is the project profitability. l
Portfolio OptimizationExample Investment PortfoliosExample Investment Portfolios2500
$)
NM
IK
KN
D2000
Gen
erat
ed ($
NM
IK
KN
DA
BD
H
AP
JO
F
HE
G
1000
1500
ativ
e N
PV G
BD
H
AP
JO
F
HE
G
l
JC
GD
H
CF
GO
EB
IM
BC
J
500
1000
Cum
ula
$1,100 MM
Started with 16 ProjectsCF
GO
EB
CG
DH
IM
BC
J
M
JL
J P LI
00 200 400 600 800 1000 1200
$400 MMWith NPV of $2,070 MM
(requires $1,165 MM Capital)LJ
M
JP L
I
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 4141
Funds Available for Investment ($)
Investment Portfolio OptimizationIdeal vs. Actual
(%)
Ideal vs. Actual
NPVo(max.)Rate of Return on
Incremental Investment (%) Marginal Costof Capital (%)
t of C
apita
l(
erat
ed ($
) NPVLRaider's Gap(NPV Loss)
Increasing Sub-optimum MARRL (%)
turn
orC
ost
NPV
Gen
e
Optimum MARRo (%)
gNPV ($)
p L ( )
Ann
ual R
et
No. ofP j t 0
Cum
.
3 4 16 NN-115 M21
OptimumBudget
LimitedBudget
Funds Available for Investment ($)
Projects00 3 4 16 NN 115 M21
Maximizing Shareholder Wealth (or MV ) requires:Optimized Capital Structure with Optimal D/E Ratio & minimized MARR
$O$L
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 4242
Optimized Capital Structure with Optimal D/E Ratio & minimized MARRMaximized Return on Existing Projects (Capital)Maximized Value Added by the New Investment Portfolio ($A w/ $Y) l
Seamlessly Collaborative StudiesPutting it all Together: Maximize Shareholders’ WealthPutting it all Together: Maximize Shareholders Wealth
ertis
e Business
Skills Integrated IDA(Business Impact
& E ti )
ow”/
Exp
& Execution)
l
Kno
w H
o
Technical
Skills
Leadership
Skills
Degree of Collaboration
“K
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 4343
Degree of Collaboration
CONCLUSIONSVALUE of Collaborated Studies
Q lifi d P f i l W kf Ed t R it
VALUE of Collaborated StudiesA Corporate Check list, Do You HAVE?
Qualified Professional Workforce – Educate, Recruit, Develop & RetainOptimized Capital Structure and Minimized Raider’s Gap
– Survival of the fittestRanked Risk Adjusted Inventory of Investment OpportunitiesppContinuous Development & Execution of Optimal Business Plan Investment Portfolios (Repeatability)Sustainable Earning GrowthSustainable Earning GrowthDistinct Competitive Advantage (Intelligent Assets)
END RESULT: Maximized Shareholders’ Value because of
Yasin Senturk, Principal Professional, Saudi April 2009 – Malaysia, Philippines and India 4444
VALUE CREATION thru Synergies Captured via Integration, Technology & Scale l
Thank you…